Creates RPC-style endpoint following layered architecture (Controller → Manager → Repository). Use when creating new API endpoints or CRUD operations.
Use this skill when the user asks to monitor a PR, watch CI, auto-merge a PR, or babysit a pull request in evot-web. Trigger phrases: "babysit pr", "watch ci", "monitor pr", "auto-merge", "/babysit-pr".
Add a new SQLite migration to the AntSeed node package. Use when adding tables, columns, or indexes to channel-store or metering databases.
Maps competitive landscape, identifies positioning gaps, and assesses competitor response capability for red-team input. Use when researching competition during BUILD phase 1 or feeding destruction phase.
Search and install agent skills from ClawHub, the public skill registry.
Use when the user needs to run GitNexus CLI commands like analyze/index a repo, check status, clean the index, generate a wiki, or list indexed repos. Examples: \"Index this repo\", \"Reanalyze the codebase\", \"Generate a wiki\
Expert guide for the NotebookLM CLI (`nlm`) and MCP server - interfaces for Google NotebookLM. Use this skill when users want to interact with NotebookLM programmatically, including: creating/managing notebooks, adding sources (URLs, YouTube, text, Google Drive), generating content (podcasts, reports, quizzes, flashcards, mind maps, slides, infographics, videos, data tables), conducting research, chatting with sources, or automating NotebookLM workflows. Triggers on mentions of \"nlm\", \"notebooklm\", \"notebook lm\", \"podcast generation\", \"audio overview\", or any NotebookLM-related automation task.
Part of the quantum-loop autonomous development pipeline (brainstorm \u2192 spec \u2192 plan \u2192 execute \u2192 review \u2192 verify). Deep Socratic exploration of a feature idea before implementation. Asks questions one at a time, proposes 2-3 alternative approaches with trade-offs, presents design section-by-section for approval, and saves an approved design document. Use when starting a new feature, exploring an idea, or before writing a spec. Triggers on: brainstorm, explore idea, design this, think through, ql-brainstorm.
Interact with GitHub using the `gh` CLI. Use `gh issue`, `gh pr`, `gh run`, and `gh api` for issues, PRs, CI runs, and advanced queries.
Thin orchestrator bootstrap prompt. Read Multorum's shipped orchestrator methodology before acting.
同步 AI 工作区文档到 iWiki、从 iWiki 回写本地、做日常增量对齐时使用。只要用户提到“同步到 iWiki”“从 iWiki 拉取”“双向更新”“补齐映射”“重传文档”“个人空间目录对齐”，都应立即使用本 Skill。
Expert guide for using the Local Falcon MCP — an AI-powered local search intelligence platform — to monitor AI visibility (ChatGPT, Gemini, Grok, Google AI Overviews, AI Mode), analyze geo-grid map rankings, evaluate AI sentiment analysis, assess competitor landscapes, and manage Google Business Profile performance. Use this skill whenever the user works with Local Falcon data including: AI search monitoring, scan reports, trend analysis, campaign management, Falcon Guard monitoring, reviews analysis, competitor research, or keyword tracking. Covers metric interpretation (SoLV, SAIV, ARP, ATRP, RVS, RQS), multi-platform analysis across 8 platforms, workflow patterns, credit-conscious scanning strategies, and actionable local SEO and AI search optimization recommendations. Also use when the user asks about AI-powered search presence, local search visibility, map pack rankings, or GBP optimization for any business. --- # Local Falcon MCP Skill ## Overview Local Falcon is an AI-powered local search intelligence platform that monitors business visibility across AI search engines (ChatGPT, Gemini, Grok, Google AI Overviews, AI Mode) and traditional map platforms (Google Maps, Apple Maps), provides AI sentiment analysis via AI-powered scan reports, and delivers deep research review reports. The Local Falcon MCP provides 37 tools for AI visibility monitoring, geo-grid ranking analysis, competitive intelligence, campaign management, GBP monitoring, review analysis, and knowledge base access. The individual tool descriptions explain what each tool does and its parameters. This skill teaches you how to think strategically about Local Falcon data: which tools to combine for common tasks, how to interpret metrics in context, and how to translate raw data into actionable recommendations. Always use the term "Google Business Profile" or "GBP." Never say "Google My Business" or "GMB" — it was rebranded in 2021. ## Core Metrics — Quick Reference ### Ranking Metrics **ARP (Average R
skill-sample/ ├─ SKILL.md ⭐ Required: skill entry doc (purpose / usage / examples / deps) ├─ manifest.sample.json ⭐ Recommended: machine-readable metadata (index / validation / autofill) ├─ LICENSE.sample ⭐ Recommended: license & scope (open source / restriction / commercial) ├─ scripts/ │ └─ example-run.py ✅ Runnable example script for quick verification ├─ assets/ │ ├─ example-formatting-guide.md 🧩 Output conventions: layout / structure / style │ └─ example-template.tex 🧩 Templates: quickly generate standardized output └─ references/ 🧩 Knowledge base: methods / guides / best practices ├─ example-ref-structure.md 🧩 Structure reference ├─ example-ref-analysis.md 🧩 Analysis reference └─ example-ref-visuals.md 🧩 Visual reference
More Agent Skills specs Anthropic docs: https://agentskills.io/home
├─ ⭐ Required: YAML Frontmatter (must be at top) │ ├─ ⭐ name : unique skill name, follow naming convention │ └─ ⭐ description : include trigger keywords for matching │ ├─ ✅ Optional: Frontmatter extension fields │ ├─ ✅ license : license identifier │ ├─ ✅ compatibility : runtime constraints when needed │ ├─ ✅ metadata : key-value fields (author/version/source_url...) │ └─ 🧩 allowed-tools : tool whitelist (experimental) │ └─ ✅ Recommended: Markdown body (progressive disclosure) ├─ ✅ Overview / Purpose ├─ ✅ When to use ├─ ✅ Step-by-step ├─ ✅ Inputs / Outputs ├─ ✅ Examples ├─ 🧩 Files & References ├─ 🧩 Edge cases ├─ 🧩 Troubleshooting └─ 🧩 Safety notes
Skill files are scattered across GitHub and communities, difficult to search, and hard to evaluate. SkillWink organizes open-source skills into a searchable, filterable library you can directly download and use.
We provide keyword search, version updates, multi-metric ranking (downloads / likes / comments / updates), and open SKILL.md standards. You can also discuss usage and improvements on skill detail pages.
Quick Start:
Import/download skills (.zip/.skill), then place locally:
~/.claude/skills/ (Claude Code)
~/.codex/skills/ (Codex CLI)
One SKILL.md can be reused across tools.
Everything you need to know: what skills are, how they work, how to find/import them, and how to contribute.
A skill is a reusable capability package, usually including SKILL.md (purpose/IO/how-to) and optional scripts/templates/examples.
Think of it as a plugin playbook + resource bundle for AI assistants/toolchains.
Skills use progressive disclosure: load brief metadata first, load full docs only when needed, then execute by guidance.
This keeps agents lightweight while preserving enough context for complex tasks.
Use these three together:
Note: file size for all methods should be within 10MB.
Typical paths (may vary by local setup):
One SKILL.md can usually be reused across tools.
Yes. Most skills are standardized docs + assets, so they can be reused where format is supported.
Example: retrieval + writing + automation scripts as one workflow.
Some skills come from public GitHub repositories and some are uploaded by SkillWink creators. Always review code before installing and own your security decisions.
Most common reasons:
We try to avoid that. Use ranking + comments to surface better skills:
